On the optimal demand-side management in microgrids through polygonal composition

This article presents a novel methodology for energy management in microgrids focused on the demand side. It is inspired by the Tangram puzzle. The energy demand and production profiles are represented by polygons and managed through computational geometry. Therefore, an optimization problem is defined to place n energy demand profiles (pieces) to cover the total energy production profile (target shape). The optimization problem is addressed with a genetic algorithm. It tries to calculate the optimal positions of the polygons of the demands covering the maximum energy production. Since the referred production comes from renewable energy sources in the microgrid, this method allows reducing both the consumption of fossil fuels and energy bills.& COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This article presents a novel methodology for energy management in microgrids through computational geometry and a genetic algorithm. By representing energy demand and production profiles as polygons, the optimal positions of demand polygons can be calculated to cover the target shape of energy production. This method reduces the consumption of fossil fuels and energy bills by utilizing renewable energy sources in microgrids.